Rate My Professor Ann Nicholson

Professor Nicholson's research focuses on artificial intelligence, particularly Bayesian networks as the dominant technology for probabilistic causal modelling and decision support under uncertainty. Her interests encompass dynamic Bayesian networks, planning under uncertainty, Bayesian inference, knowledge engineering, and applications in medicine, epidemiology, environmental science, biosecurity, and meteorology. She has published over 120 peer-reviewed papers and co-authored the seminal textbook Bayesian Artificial Intelligence (second edition, 2010, with Kevin B. Korb), which has received nearly 3000 citations. Other highly cited works include Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment (2007, 603 citations), Dynamic Time Warping averaging of time series allows faster and more accurate classification (2014, 360 citations), and Modeling COVID-19 disease processes by remote elicitation of causal Bayesian networks from medical experts (2023). She has secured more than $12 million in research funding, founded two start-up companies, and demonstrated significant impact with over 7000 citations across her publications. Her honors include the Rhodes Scholarship (1988), Fellowship of the Australian Academy of Technological Sciences & Engineering (2022), and the IEEE International Conference on Data Mining 10-year Highest Impact Award (2023, shared with Geoff Webb).